Statistical Methods for Survival Data Analysis: Elisa T. Lee and John Wenyu Wang

Lee, Elisa T.; Wang, John Wenyu

ISBN 10: 0471369977 / ISBN 13: 9780471369974

Verlag: Wiley-Interscience (edition Subsequent), 2003

Beschreibung

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Bestandsnummer des Verkäufers 0471369977-11-1

Bibliografische Details

• Titel: Statistical Methods for Survival Data Analysis: Elisa T. Lee and John Wenyu Wang
• Verlag: Wiley-Interscience (edition Subsequent)
• Erscheinungsjahr: 2003
• Sprache: Englisch
• ISBN-10: 0471369977
• ISBN-13: 9780471369974
• Einband: Hardcover
• Auflage: Subsequent.
• Zustand: Good

Über diesen Titel

Inhaltsangabe

Third Edition brings the text up to date with new material and updated references. New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.

Über die Autorin bzw. den Autor

ELISA T. LEE, PhD, is George Lynn Cross Research Professor of Biostatistics and Epidemiology and Director of the Center for American Indian Health Research at the University of Oklahoma Health Sciences Center. She received a master's degree from the University of California at Berkeley and her doctorate from New York University. The author of the previous editions of Statistical Methods for Survival Data Analysis, Professor Lee is a Fellow of the American Statistical Association and member of the Society for Epidemiological Research and the American Diabetes Association. JOHN WENYU WANG, PhD, is an Associate Professor of Biostatistics at the University of Oklahoma Health Sciences Center. He received a master's degree from the Academy of Sciences of China and his doctorate from the University of Maryland.